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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Femtosecond MeV Electron Energy-Loss Spectroscopy

Pump-probe electron energy-loss spectroscopy (EELS) with femtosecond temporal resolution will be a transformative research tool for studying nonequilibrium chemistry and electronic dynamics of matter. Here in this article, we propose a concept of femtosecond EELS utilizing mega-electron-volt electron beams from a radio-frequency (rf) photocathode source. The high acceleration gradient and high beam energy of the rf gun are critical to the generation of 10-fs electron beams, which enables an improvement of the temporal resolution by more than 1 order of magnitude beyond the state of the art. In our proposal, the “referencebeam technique” relaxes the energy stability requirement of the rf power source by roughly 2 orders of magnitude. The requirements for the electron-beam quality, photocathode, spectrometer, and detector are also discussed. Supported by particle-tracking simulations, we demonstrate the feasibility of achieving subelectron- volt energy resolution and approximately 10-fs temporal resolution with existing or near-future hardware performance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Detecting Hardware Trojans in PCBs Using Side Channel Loopbacks

Malicious modifications to printed circuit boards (PCBs) are known as hardware Trojans. These may arise when malafide third parties alter PCBs premanufacturing or postmanufacturing and are a concern in safety-critical applications, such as industrial control systems. In this research, we examine how data-driven detection can be utilized to detect such Trojans at run-time. We develop a flexible and reconfigurable PCB test bed derived from the popular open-source programmable logic controller (PLC) platform “OpenPLC.” We then develop a Trojan detection framework, which utilizes and analyzes multimodal side channels (e.g., timing, magnetic signals, power, and hardware performance counters). We consider defender-configurable input/output (I/O) loopback test, comparison with design-document baselines, and magnetometer-aided monitoring of system behavior under defender-chosen excitations. Our approach can extend to golden-free environments. Golden (known-good) versions of the PCBs are assumed not available, but design information, datasheets, and component-level data are available. We demonstrate the efficacy of our approach on a range of Trojans instantiated in the test bed.

42 ENGINEERING↗
DOE OSTI2024

TEAMER: Drifting Hydrophone System - Block Diagram and Pre-Amplifier Calibrations

This data release is part of TEAMER RFTS 2, where the Cooperative Institute for Marine Resources Studies (CIMRS) at Oregon State University is performing hardware and software development and integration of four newly designed drifting hydrophone systems for underwater noise measurements at marine renewable energy projects. These new acoustic systems will provide advanced technology support available for use at both tidal and wave energy deployments adding additional resources to the limited amount of drifting hydrophone technologies that are available to the marine energy community The submission data contains 2 files plus a Post-Access Report: One file containing the calibration parameters for four (4) pre-amplifier boards used on the drifting hydrophones. Pre-amplifier boards are model "WB PREAMP REV6," with serial numbers; 28, 29, 30, and 31. One image file illustrating the system functional block diagram of the drifting hydrophone system configuration.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

The Muon g-2 Experiment [Slides]

$a_{\mu} \equiv (g-2)/2$, most recently at Brookhaven National Lab (E821) in the early 2000s, differ from theoretical calculations by nearly 3.5\,$\sigma$. To address this discrepancy, the Muon $g-2$ Experiment at Fermilab (E989) has been designed to determine $a_{\mu}$ to a precision of 140 parts per billion, a four-fold improvement over the E821 measurement. This improved precision presents an excellent opportunity to uncover new physics beyond the standard model (BSM), and at minimum constrain BSM models. The E989 experiment is currently taking physics-quality data, to date having recorded nearly 60\% more statistics than was obtained at Brookhaven. An overview of the experimental technique will be discussed, along with an update of the run progress and selected hardware performance and analysis highlights.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Turboexpander for Direct Cooling in Hydrogen Vehicle Fueling Infrastructure

Hydrogen fuel cell electric vehicles (FCEVs) have been identified as one of a few options for zero carbon emissions transportation. A major advantage of FCEVs is that they can fuel quickly and follow a familiar fueling behavior to hydrocarbon-fueled vehicles. Whether light duty or heavy duty, the goal for a hydrogen dispenser is to fuel a vehicle in the same amount of time as the fossil fuel equivalent. When hydrogen is dispensed into the vehicle storage system, however, the temperature rises due to the Joule-Thomson effect and the heat of compression. Typically, vehicles store the compressed hydrogen in composite overwrapped pressure vessels that have a polymer liner with an operational temperature limit of 85°C. This temperature limit can be exceeded during fast fueling if hydrogen is not precooled. Precooling allows for a dispenser to fuel a vehicle at a faster flow rate by preventing the storage tank on the vehicle from overheating. Fueling protocols and requirements are presented in SAE J2601 Fueling Protocols for Light Duty Gaseous Hydrogen Surface Vehicles [1]. A heavy-duty equivalent is under development with similar requirements for precooling. Currently, conventional precooling for light-duty vehicle refueling uses a heat exchanger and chiller to cool the hydrogen gas to -40°C before entering the vehicle. The precooling system represents a significant part of the station capital and operating costs, so if the cost of the precooling system can be reduced by improving its efficiency, the overall station capital and operating cost can be reduced. In this project, National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (SNL) researchers teamed up to investigate the turboexpander precooling application. A turboexpander is a device that places a turbine in a flow path where a pressure differential can be attained. This expansion device will extract work and lower the temperature of the fluid as the pressure reduces. While initial calculations based on established principles showed potential for a turboexpander to generate cooled gas, much work needs to be done to prove the concept. Turboexpanders typically work best under steady state conditions, while the dispenser is a very dynamic flow system. Dynamic turboexpander systems have been proven, such as a turbocharger on a gasoline vehicle. The inlet pressure at a dispenser is also much higher than any other known turboexpander system but should behave similarly to higher density fluids at lower pressures. Having both performed initial calculations, NREL and SNL researchers teamed up to investigate the turboexpander precooling application further. A project was soon built around the idea with SNL performing system modeling using previously proven capabilities and NREL performing hardware characterization with established station capabilities. Creare LLC was contracted as the turbomachinery expert to design and build the concept device. Part way through the project, however, contracting issues with the funding partner caused the project to terminate early before building and characterizing the concept device. While the project could not continue, many key findings were already learned. This paper is a summary of those findings.

08 HYDROGEN↗
DOE OSTI2024

Drop Tower Statement of Work

This document details the needs and requirements for a propulsion-assisted drop tower system (further referenced simply as Drop Tower) to perform hardware testing at Lawrence Livermore National Laboratory (LLNL). LLNL is managed and operated by Lawrence Livermore National Security, LLC (LLNS) for the Department of Energy (DOE). LLNL requires a robust testing platform that will allow for the characterization of interactions between objects of interest. The initial siting of the equipment will be located in an existing test facility (B191). When another test facility becomes online, the objective will be to move the test capability to the new facility as a final location (B132N). The Drop Tower will be a cornerstone capability for testing and model validation for LLNL interested programs.

42 ENGINEERING↗
DOE OSTI2025

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

Neural Architecture Search is a powerful approach for automating model design, but existing methods struggle to accurately optimize for real hardware performance, often relying on proxy metrics such as bit operations. We present Surrogate Neural Architecture Codesign Package (SNAC-Pack), an integrated framework that automates the discovery and optimization of neural networks focusing on FPGA deployment.

Weitz, Jason [UC, San Diego]↗
DOE OSTI2019

Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer

We present the application of Restricted Boltzmann Machines (RBMs) to the task of astronomical image classification using a quantum annealer built by D-Wave Systems. Morphological analysis of galaxies provides critical information for studying their formation and evolution across cosmic time scales. We compress the images using principal component analysis to fit a representation on the quantum hardware. Then, we train RBMs with discriminative and generative algorithms, including contrastive divergence and hybrid generative-discriminative approaches. We compare these methods to Quantum Annealing (QA), Markov Chain Monte Carlo (MCMC) Gibbs Sampling, Simulated Annealing (SA) as well as machine learning algorithms like gradient boosted decision trees. We find that RBMs implemented on D-wave hardware perform well, and that they show some classification performance advantages on small datasets, but they don't offer a broadly strategic advantage for this task. During this exploration, we analyzed the steps required for Boltzmann sampling with the D-Wave 2000Q, including a study of temperature estimation, and examined the impact of qubit noise by comparing and contrasting the original D-Wave 2000Q to the lower-noise version recently made available. While these analyses ultimately had minimal impact on the performance of the RBMs, we include them for reference.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Peak Prediction Using Multi Layer Perceptron (MLP) for Edge Computing ASICs Targeting Scientific Applications

High data rate detectors play an integral part in scientific research and their development is actively pursued at High Energy Physics (HEP) facilities around the world. Edge Machine Learning (ML) offers the ability to reduce data rates by integrating ML algorithms into Application Specific Integrated Circuits (ASICs) on the front end electronics. In this work, we explore a set of neural network architectures for predicting the peak amplitudes in the detector's sensor response. We have designed and synthesized several MLP based neural networks comparing their inference accuracy, power consumption, and area targeting for minimal latency. The neural networks are synthesized in a commercial 65nm process. The effect of quantizing the network's weights and biases on hardware performance and area is reported. We also conduct design space exploration to compare between design alternatives

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs

It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large datasets. Unfortunately, moving scientific applications between HPC systems is challenging for various reasons, most notably that HPC systems have different HPC schedulers. We introduce PSI/J, a job management abstraction API intended to simplify the construction of software components and applications that are portable over various HPC scheduler implementations. We argue that such a system is both necessary and that no viable alternative currently exists. We analyze similar notable APIs and attempt to determine the factors that influenced their evolution and adoption by the HPC community. We base the design of PSI/J on that analysis. We describe how PSI/J has been integrated in three workflow systems and one application, and also show via experiments that PSI/J imposes minimal overhead.

Hategan, Mihael↗
DOE OSTI2024

Offshore Wind to Hydrogen - Modeling, Analysis, Testing and International Collaboration Work

This project explores electrolytic hydrogen production from an offshore wind turbine by: Modeling: Simulate an offshore wind turbine and generate power output profiles; Analysis: Analyze offshore conditions and determine operational modes of the stack; Testing: Perform hardware testing to evaluate dynamic characteristics; and International Collaboration Work: Share learnings and publish. Potential Outcomes: Accelerate development of an integrated, in-turbine offshore wind hydrogen system; and Support two DOE Energy Earthshots - Hydrogen and Floating Offshore Wind.

electrolyzer↗
DOE OSTI2025

Summer 2025 SULI: Nucleus ID, TinyTPC, and Scientific Communication

This paper summarizes my work during the Summer 2025 SULI internship, which focused on two main projects and broader scientific development. The first project involved improving the particle identification (PID) of protons, deuterons, and tritons using PIDA distributions and template fitting, with the goal of modeling nuclear final-state interactions (FSI) and testing the robustness of the method against systematic uncertainties. These techniques pave the way for future application to LArTPC data from the ICARUS detector. The second project centered on the optimization and data-taking of the TinyTPC detector, a compact LArTPC used for high-resolution low-energy measurements. I adjusted gain and threshold parameters, performed hardware validation tests, and developed analysis strategies to extract meaningful physics from collected data. Throughout the summer, I also enhanced my scientific communication and mentorship skills through presentations, collaborative analysis, and peer guidance.

McCright, Hannah [Maryland U.]↗
DOE OSTI2020

Processing unit performance projection using dynamic hardware behaviors

Methods for estimating accelerator performance for dynamic hardware behaviors are disclosed. Computer program code to be executed on a first processing unit is received, and an execution of the computer code on the first processing unit is monitored to determine a plurality of performance characteristics. A plurality of dynamic hardware behaviors is determined by applying a clustering algorithm to the performance characteristics, and an equivalent accelerator portion of computer code to be executed on a second processing unit is generated by translating a set of instructions in a first portion of computer code corresponding to a first one of the plurality of dynamic hardware behaviors to an equivalent set of instructions to be executed on the second processing unit. An estimated measure of performance for executing the equivalent accelerator portion on the second processing unit is determined for the first one of the plurality of dynamic hardware behaviors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantum-Hardware Focused Application Performance Benchmarks (Final Technical Report)

Quantum computers promise to transform how we do scientific calculations. In this project, we benchmark different current quantum computers for solving chemistry problems and find ways to build noise-resilient implementations. We also use the characterization techniques developed to test ion trap quantum computers.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Hardware Selection and Performance of Low-Cost Fluorometers

Access to and extensive use of fluorometric analyses is limited, despite its extensive utility in environmental transport and fate. Wide-spread application of fluorescent tracers has been limited by the prohibitive costs of research-grade equipment and logistical constraints of sampling, due to the need for high spatial resolutions and access to remote locations over long timescales. Recently, low-cost alternatives to research-grade equipment have been found to produce comparable data at a small fraction of the price for commercial equipment. Here, we prototyped and benchmarked performance of a variety of fluorometer components against commercial units, including performance as a function of tracer concentration, turbidity, and temperature, all of which are known to impact fluorometer performance. While component performance was found to be comparable to the commercial units tested, the best configuration tested obtained a functional resolution of 0.1 ppb, a working concentration range of 0.1 to >300 ppb, and a cost of USD 59.13.

42 ENGINEERING↗